Jesse Davis

News

Research

Software

• Jesse Davis, Vitor Santos Costa, Soumya Ray and David Page (2007). An Integrated Approach to Feature Construction and Model Building for Drug Activity Prediction. To appear in the Proceedings of the 24th International Conference on Machine Learning (ICML). Available as PDF.

• Jesse Davis, Irene Ong, Jan Struyf, Elizabeth Burnside, David Page and Vitor Santos Costa (2007). Change of Representation for Statistical Relational Learning. In the Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI). Available as PDF.

• Jesse Davis and Mark Goadrich (2006). The Relationship Between Precision-Recall and ROC Curves. In the Proceedings of the 23rd International Conference on Machine Learning (ICML). Available as PDF.

• Jan Struyf, Jesse Davis and David Page (2006). An Efficient Approximation to Lookahead in Relational Learners. In the Proceedings of the 17th European Conference on Machine Learning (ECML). Available as PDF.

• Jesse Davis, Elizabeth Burnside, Ines Dutra, David Page, Raghu Ramakrishnan, Vitor Santos Costa and Jude Shavlik (2005). View Learning for Statistical Relational Learning: With an Application to Mammography. In the Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI). Available as postscript or PDF or Presentation.

• Jesse Davis, Ines Dutra, David Page and Vitor Santos Costa (2005). Establishing Identity Equivalence in Multi-Relational Domains. In the Proceedings of the International Conference on Intelligence Analysis. Available as postscript, PDF or Word. Winner of the Best Technical Paper award.

• Elizabeth S. Burnside, Jesse Davis, Vitor Santos Costa, Ines Dutra, Charles E. Kahn Jr., Jason P. Fine and David Page (2005). Knowledge Discovery from Structured Mammography Reports Using Inductive Logic Programming. In the Proceeding of the American Medical Informatics Association Annual Symposium (AMIA) . Will be available shortly.

• Jesse Davis, Elizabeth Burnside, Ines Dutra, David Page, Vitor Santos Costa (2005). An Integrated Approach to Learning Bayesian Networks of Rules. In the Proceedings of the European Conference of Machine Learning (ECML). Available as postscript or PDF.

Book Chapters

• Jesse Davis, Elizabeth Burnside, Ines Dutra, David Page, Raghu Ramakrishnan, Vitor Santos Costa and Jude Shavlik (2006). Learning a New View of a Database: With an Application to Mammography. To appear in L. Getoor and B. Taskar, editors, An Introduction to Statistical Relational Learning, MIT Press.

Refereed Workshops

• Jesse Davis, Elizabeth Burnside, David Page and Vitor Santos Costa (2006). View Learning Extended: Inventing New Tables for Statistical Relational Learning. In the Proceedings of Open Problems in Statistical Relational Learning Workshop (SRL2006). In conjunction with ICML 2006.

• Jesse Davis, Vitor Santos Costa, Irene Ong, David Page and Ines Dutra (2004). Using Bayesian Classifiers to Combine Rules. Appears in the Proceedings of the 3rd Workshop on Multi-Relational Data Mining ( MRDM 2004). In conjunction with KDD 2004. Available as postscript or PDF.

Professional Service

• Program Committee for AAAI(2008)
• Program Committee for International Conference on Machine Learning (ICML)(2008)
• Reviewer for ACM Transactions on Knowledge Discovery from Data (2007)
• Reviewer for Journal of Artificial Intelligence Research (2007)
• Reviewer for Machine Learning Journal (2007)
• Reviewer for 15th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB-07)
• Reviewer for the 20th International Joint Conference on Artificial Intelligence (IJCAI-07)
• Reviewer for ACM Transactions on Computational Logic (2006)

Past Teaching Experience

• Spring 2003: Discussion Leader for CS302: Introduction to Programming Sections 303 and 304.
  
• Fall 2002: Discussion Leader for for CS302: Introduction to Programming Section 314.
  

Education

• M.S. in Computer Science, University of Wisconsin, Madison, May 2005.
  
  Courses taken:
  

  Spring 2005

  • CS784: Data Models and Languages with Raghu Ramakrishnan.
  • Genetics 466: General Genetics.

  Fall 2004

  • CS520: Introduction to Theorectical Computer Science with Jin-Yi Cai.
  • CS701: with Susan Horwitz.

  Spring 2004

  • MATH541: Modern Algebra 1 with Arnold Johnson
  • MATH475: Combinatorics with James Propp

  Fall 2003

  • CS576: Introduction to Bioinformatics with Mark Craven.
  • CS764: Topics in Database Systems with Jeffrey Naughton.

  Spring 2003

  • CS760: Machine Learning with Jude Shavlik.
  • CS564: Database Management Systems: Design and Implementation with Jeff Naughton.

  Fall 2002

  • CS537: Introduction to Operating Systems with Marvin Solomon.
  • CS731: Advanced Artificial Intelligence with Biomedical Applications with David Page.
  
  
• B.A. in Computer Science, from Williams College, June 2002.

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